An Early Warning of Heart Attack

An Early Warning of Heart Attack

Early-warning system: Each patient’s blood is analyzed using a mass spectrometer and a technique known as multiplexing. The presence of several dozen metabolites can diagnose a heart attack within 10 minutes.

A new method for diagnosing heart attacks very early on could improve a patient’s chances of survival and reduce the amount of permanent damage that he or she suffers. Normally, it takes up to six hours to diagnose a heart attack with certainty. The new approach can do so in just 10 minutes by analyzing tiny biochemical markers in the blood, such as lipids, sugars, and amino acids–a technique known as metabolic profiling.

Heart attacks occur when the heart’s blood supply is interrupted, usually because of some sort of blockage within the artery. “Interventions are most effective in the first few hours, and their effectiveness falls off with time,” says Robert Gerszten, director of translation research in the cardiology division of Massachusetts General Hospital, in Boston, who led development of the new test. “Time equals injury.”

Diagnosis normally involves a physical examination, an electrocardiogram, and blood tests that look for key metabolites, including the protein complex troponin. However, this can take many hours: troponin is an indication of cardiac damage and therefore does not show up until hours after an attack. Once a heart attack has been confirmed, a patient can be given more-effective treatments such as beta blockers and anticoagulation drugs. But it is important to get the diagnosis right, as treating someone for a heart attack when he hasn’t had one can cause further health complications, says Andrew Grace, a cardiologist at Papworth Hospital, in Cambridge, U.K. “There are all kinds of long-term implications in terms of insurance and the patient’s state of mind that require [accurate] diagnosis,” Grace adds.

There has already been a lot of interest in using metabolic profiling to diagnose disease, says Gerszten. But it can be problematic because metabolites vary significantly from one individual to another, and even within the same person, depending on what he or she has eaten.

To address this issue, Gerszten and his colleagues took advantage of a treatment administered for a heart condition called hypertrophic cardiomyopathy. “Patients with hypertrophic cardiomyopathy actually benefit from a planned heart attack,” says Gerszten. The treatment involves injecting alcohol into part of the heart to cause a small, controlled heart attack that destroys excess tissue that is causing problems.

This setup also provides a unique opportunity to detect the metabolites related to heart attacks. By taking blood samples from 36 patients before and after they underwent the procedure, Gerszten’s team was able to screen out background metabolites and determine exactly which ones emerged directly after the attack.

Each patient’s blood was analyzed using a mass spectrometer and a technique known as multiplexing, which allows a large number of metabolites to be screened almost simultaneously. Within 10 minutes, the blood was analyzed for 210 metabolites, and the results were compared with those found in the blood before the heart attack. “It’s a subtractive analysis,” says Gerszten. “That’s the beauty of this setup: each person is their own biological control.”

Data gathered from 20 of the patients provided a signature of several dozen metabolites. This signature was then validated against the remaining 16 patients, as well as against an additional 12 ER patients who had suffered spontaneous heart attacks. Gerszten’s team found that the signature could be used to identify heart attacks with an accuracy of greater than 80 percent. The results of his study are published in the Journal of Clinical Investigation.

Gerszten plans to extend his research to include many more patients. If precursor biomarkers can be identified, the hope is that this sort of technique could ultimately be used to predict heart attacks, and hence possibly even avert them.